In [11]:
import numpy as np 
import pandas as pd 
import pandas_profiling as pp
import altair as alt
from altair import Chart, X, Y, Axis, SortField
from vega_datasets import data
from altair import expr, datum
from altair.expr import datum
# for the notebook only (not for JupyterLab) run this command once per session
alt.renderers.enable('notebook')
alt.data_transformers.enable('default', max_rows=None)
Out[11]:
DataTransformerRegistry.enable('default')
In [12]:
alt.data_transformers.enable('default', max_rows=None)
Out[12]:
DataTransformerRegistry.enable('default')
In [13]:
df_winter = pd.read_csv('winter.csv')
df_summer = pd.read_csv('summer.csv')
df_sumandwint = pd.read_csv('sumandwint.csv')
df_dictionary = pd.read_csv('dictionary.csv')
In [14]:
df_summer.head()
Out[14]:
Year City Sport Discipline Athlete Country Gender Event Medal
0 1896 Athens Aquatics Swimming HAJOS, Alfred HUN Men 100M Freestyle Gold
1 1896 Athens Aquatics Swimming HERSCHMANN, Otto AUT Men 100M Freestyle Silver
2 1896 Athens Aquatics Swimming DRIVAS, Dimitrios GRE Men 100M Freestyle For Sailors Bronze
3 1896 Athens Aquatics Swimming MALOKINIS, Ioannis GRE Men 100M Freestyle For Sailors Gold
4 1896 Athens Aquatics Swimming CHASAPIS, Spiridon GRE Men 100M Freestyle For Sailors Silver
In [15]:
df_dictionary.head()
Out[15]:
Country Code Population GDP per Capita CountryName City CapitalLatitude CapitalLongitude CountryCode ContinentName
0 Afghanistan AFG 32526562.0 594.323081 Afghanistan Kabul 34.516667 69.183333 AF Asia
1 Albania ALB 2889167.0 3945.217582 Albania Tirana 41.316667 19.816667 AL Europe
2 Algeria ALG 39666519.0 4206.031232 Algeria Algiers 36.750000 3.050000 DZ Africa
3 American Samoa* ASA 55538.0 NaN American Samoa Pago Pago -14.266667 -170.700000 AS Australia
4 Andorra AND 70473.0 NaN Andorra Andorra la Vella 42.500000 1.516667 AD Europe
In [6]:
summer_with_country_winner  = pd.merge(df_summer, 
                  df_dictionary[['CountryName','Code','ContinentName']],
                  left_on='Country',
                  right_on='Code',
                  how='left')
summer_with_country_winner.drop(['Country'], axis=1)
summer_with_code  = pd.merge(summer_with_country_winner, 
                  df_dictionary[['City','Country', 'CapitalLatitude','CapitalLongitude','ContinentName']],
                  on='City',
                  how='left')
In [7]:
top_countries = summer_with_code['Country_x'].value_counts()[:25].index.tolist()
In [8]:
filtered_summer = summer_with_code[summer_with_code['Country_x'].isin(top_countries)].reset_index()
In [9]:
filtered_summer.head()
Out[9]:
index Year City Sport Discipline Athlete Country_x Gender Event Medal CountryName Code ContinentName_x Country_y CapitalLatitude CapitalLongitude ContinentName_y
0 0 1896 Athens Aquatics Swimming HAJOS, Alfred HUN Men 100M Freestyle Gold Hungary HUN Europe Greece 37.983333 23.733333 Europe
1 6 1896 Athens Aquatics Swimming HAJOS, Alfred HUN Men 1200M Freestyle Gold Hungary HUN Europe Greece 37.983333 23.733333 Europe
2 11 1896 Athens Athletics Athletics LANE, Francis USA Men 100M Bronze United States USA Central America Greece 37.983333 23.733333 Europe
3 12 1896 Athens Athletics Athletics SZOKOLYI, Alajos HUN Men 100M Bronze Hungary HUN Europe Greece 37.983333 23.733333 Europe
4 13 1896 Athens Athletics Athletics BURKE, Thomas USA Men 100M Gold United States USA Central America Greece 37.983333 23.733333 Europe
In [10]:
select_box = alt.binding_select(options=list(summer_with_code['Sport'].unique()))
selection_box = alt.selection_single(name='Select', fields=['Sport'], bind=select_box)

bar_chart = alt.Chart(filtered_summer).mark_bar(size=15).encode(
    x=alt.X('count()', axis=alt.Axis(title='The number of medals')),
    y=alt.Y('Country_x:N', sort=alt.EncodingSortField(field='Medal', order='descending', op='count'),
        axis=Axis(title='Countries')),
    color=alt.Color('Medal:N', scale=alt.Scale(range=["#ffd700", "#c0c0c0", "#cd7f32"]), sort=['Gold', 'Silver','Bronze']),
    order=alt.Order('Medal', sort='descending'),
).add_selection(
    selection_box,
).transform_filter(
    selection_box 
).configure_axis(
    labelFont='Lato Regular', labelColor='#5d646f', labelFontSize=12,
    titleFont='Lato Regular Italic', titleFontSize=14, grid=True, gridColor='#5d646f', gridDash=[0.5, 0.5, 0.5], gridOpacity=0.4               
).properties(
    width=700,
    height=550, padding=30,
    title = alt.TitleParams(text = 'Top countries in each sport', anchor='start',
                            font = 'Lato Bold', fontSize = 18, color = '#3E454F')
)

from IPython.display import HTML
display(HTML("""
<style>
.vega-embed{
    position: relative;
}
.vega-bind {
  position: relative;
  top: -520px;
  left: 780px;
  display: inline;
}
select {
    width: 100px;
}
.vega-bind-name{
    padding-right: 5px;
}
</style>
"""))
display(bar_chart)











    


























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